Better Data for Better Science

The Brief

The Center for Expanded Data Annotation and Retrieval (CEDAR) is a collaboration between Stanford Medicine, University of Oxford, Northrop Grumman, and Yale University. They have developed information technologies that make authoring complete metadata much more manageable, and that facilitate using the metadata in further scientific and medical research. The project goal is to help investigators achieve the promise of Big Data. To do this, we built a system that uses computers to make life better for biomedical researchers providing and using metadata. People can now use the CEDAR tools to create or search templates or metadata for their research.

MJD worked with Stanford providing strategy, user experience research and documentation, user interface design and testing, and an innovative Symfony/Angular headless technology framework.

Strategies

We believe ease of use is paramount. Because the ability to share data is so important, we wanted the process of metadata creation and use to be as painless as possible. Our strategic approach addressed the challenges we have seen in other similar projects.

Six key elements contribute to what we believe will be a successful system:

Interfaces and tools built and tested specifically for metadata creation

Consistency in terminology

Machine learning

Editing capabilities

Training and outreach

Building on past work and leveraging ongoing collaborations

Extensive prototyping and testing was undertaken to ensure that the six key elements were successful.

Building the Platform

After the UX/UI prototypes were built and tested, we began to build the system. We created a custom content management and data repository system using Symfony and Angular. We designed and built an API that allowed metadata to flow into and out from the system, making it easy for researchers to create forms for research studies that are inherently tagged with data readable by anyone around the world in a consistent way.

Results

The world’s first consistent terminology tool for medical research metadata

Utilization of machine learning to analyze Big Data to make research data available worldwide in real time